Computational complexity reduction for MIMO-OFDM channel estimation algorithms

Channel estimation algorithms have a key role in signal detection in MIMO-OFDM systems. In this system, the number of channel components which need to be estimated is much more than conventional SISO wireless systems. Consequently, the computational process of channel estimation is highly intensive....

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Main Authors: Abdolee, Reza, Abd. Rahman, Tharek, Idrus Sutan Nameh, Sevia Mahdaliza
Format: Article
Language:English
Published: Faculty of Electrical Engineering 2007
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Online Access:http://eprints.utm.my/id/eprint/8217/1/TharekAbdRahman2007_Computational_complexity_reduction_for_MIMO-OFDM_channel.pdf
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http://portal.psz.utm.my/psz/index.php?option=com_content&task=view&id=128&Itemid=305&PHPSESSID=7300e2779d93ea9f1bf702614ffa203c
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Institution: Universiti Teknologi Malaysia
Language: English
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spelling my.utm.82172010-06-02T01:52:46Z http://eprints.utm.my/id/eprint/8217/ Computational complexity reduction for MIMO-OFDM channel estimation algorithms Abdolee, Reza Abd. Rahman, Tharek Idrus Sutan Nameh, Sevia Mahdaliza TK Electrical engineering. Electronics Nuclear engineering Channel estimation algorithms have a key role in signal detection in MIMO-OFDM systems. In this system, the number of channel components which need to be estimated is much more than conventional SISO wireless systems. Consequently, the computational process of channel estimation is highly intensive. In addition, the high performance channel estimation algorithms mostly suffer from high computational complexity. In the other words, the system undergoes intensive computations if high performance efficiency is desired. However, there is an alternative solution to achieve both high performance efficiency and relatively low level of computational complexity. In this solution, high efficient channel estimation is firstly designed, and then it is simplified using alternative mathematical expressions. In this research, QR decomposition (QRD) as an alternative mathematical expression to alleviate the computational complexity of those complex algorithms which need matrix inversion is investigated. Herein, the channel estimation algorithm which is targeted to simplify is Least Square (LS) method. The results show QR decomposition can greatly reduce the complexity of LS channel estimation. As an example, for particular scenario, it achieves reduction of computational complexity as much as 77% while it keeps the performance efficiency of the system at the same level. Faculty of Electrical Engineering 2007 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/8217/1/TharekAbdRahman2007_Computational_complexity_reduction_for_MIMO-OFDM_channel.pdf Abdolee, Reza and Abd. Rahman, Tharek and Idrus Sutan Nameh, Sevia Mahdaliza (2007) Computational complexity reduction for MIMO-OFDM channel estimation algorithms. Elektrika, 9 (1). pp. 30-36. ISSN 0128-4428 http://portal.psz.utm.my/psz/index.php?option=com_content&task=view&id=128&Itemid=305&PHPSESSID=7300e2779d93ea9f1bf702614ffa203c
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Abdolee, Reza
Abd. Rahman, Tharek
Idrus Sutan Nameh, Sevia Mahdaliza
Computational complexity reduction for MIMO-OFDM channel estimation algorithms
description Channel estimation algorithms have a key role in signal detection in MIMO-OFDM systems. In this system, the number of channel components which need to be estimated is much more than conventional SISO wireless systems. Consequently, the computational process of channel estimation is highly intensive. In addition, the high performance channel estimation algorithms mostly suffer from high computational complexity. In the other words, the system undergoes intensive computations if high performance efficiency is desired. However, there is an alternative solution to achieve both high performance efficiency and relatively low level of computational complexity. In this solution, high efficient channel estimation is firstly designed, and then it is simplified using alternative mathematical expressions. In this research, QR decomposition (QRD) as an alternative mathematical expression to alleviate the computational complexity of those complex algorithms which need matrix inversion is investigated. Herein, the channel estimation algorithm which is targeted to simplify is Least Square (LS) method. The results show QR decomposition can greatly reduce the complexity of LS channel estimation. As an example, for particular scenario, it achieves reduction of computational complexity as much as 77% while it keeps the performance efficiency of the system at the same level.
format Article
author Abdolee, Reza
Abd. Rahman, Tharek
Idrus Sutan Nameh, Sevia Mahdaliza
author_facet Abdolee, Reza
Abd. Rahman, Tharek
Idrus Sutan Nameh, Sevia Mahdaliza
author_sort Abdolee, Reza
title Computational complexity reduction for MIMO-OFDM channel estimation algorithms
title_short Computational complexity reduction for MIMO-OFDM channel estimation algorithms
title_full Computational complexity reduction for MIMO-OFDM channel estimation algorithms
title_fullStr Computational complexity reduction for MIMO-OFDM channel estimation algorithms
title_full_unstemmed Computational complexity reduction for MIMO-OFDM channel estimation algorithms
title_sort computational complexity reduction for mimo-ofdm channel estimation algorithms
publisher Faculty of Electrical Engineering
publishDate 2007
url http://eprints.utm.my/id/eprint/8217/1/TharekAbdRahman2007_Computational_complexity_reduction_for_MIMO-OFDM_channel.pdf
http://eprints.utm.my/id/eprint/8217/
http://portal.psz.utm.my/psz/index.php?option=com_content&task=view&id=128&Itemid=305&PHPSESSID=7300e2779d93ea9f1bf702614ffa203c
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